Quantum AI drives next-gen enterprise decision-making – News

From smarter factories to predictive supply chains, artificial intelligence is entering a new phase, powered in part by quantum AI and its ability to tackle problems too complex for classical computing.

As enterprises move past the hype of generative models, they’re embracing a future built on intelligent agents, digital twins and high-dimensional simulations. The emphasis is shifting from experimentation to execution, where AI systems must not only generate content, but make reliable decisions, earn trust and deliver measurable impact across industries, according to Scott Hebner (pictured, right), principal analyst for AI for business, agents, explainability, decision intelligence  and causal AI at theCUBE Research.

“Gen AI is kind of the same thing,” he said. “It’s a gateway into the world of AI. But it doesn’t really allow you to make decisions. That’s what I thought was the real focus here … we’re going to build on gen AI.”

Hebner and Paul Gillin (center), enterprise editor at News, spoke with theCUBE host Rebecca Knight (left) at SAS Innovate, as a part of the keynote analysis during an exclusive broadcast on theCUBE, News Media’s livestreaming studio. They discussed how AI, specifically quantum AI, is advancing from generative capabilities to decision-making tools that drive real-world outcomes in enterprise settings — and SAS Institute Inc.’s mission role in driving effective solutions. (* Disclosure below.)

The role of quantum AI in shaping enterprise decision intelligence

The event made clear that quantum AI is no longer a distant concept. Companies such as The Procter & Gamble Co. are already applying it to high-stakes challenges, including product safety and dynamic inventory management. These solutions depend on intense compute power to handle problems with more permutations than atoms in the universe, according to Hebner.

“Quantum’s going to help solve these highly dimensional, super complex data intensive workloads, because you need that compute power,” he said. “We’re just going to optimize it through our pre-built models and agents and services around your industry.”

This quantum approach, however, doesn’t stand alone. In practice, SAS showcased a hybrid AI model combining quantum and traditional methods, significantly reducing computation time while maintaining acceptable levels of data quality. This kind of pragmatic application underscores a broader shift in AI development, from aspirational visions to measurable business outcomes.

“They got it down to two minutes with pure quantum, but there were reliability problems,” Gillin said. “So, they did a hybrid approach that got it down to 12 minutes where the data quality was sufficient and the speed was acceptable.”

Building trust remains a central challenge. Without reliable systems, AI cannot deliver on its promise of decision intelligence. The emphasis on governance, human oversight and ecosystem collaboration echoed throughout the event. Experts stressed that while agents can act autonomously, the role of human judgment is more vital than ever, especially as systems become more complex and intertwined with business operations, according to Hebner.

“In the end, agents are only going to be as good as people trust them,” he added. “If they’re supposed to be digital coworkers and you’re going to be partnering to make decisions … people have to trust it. Trust is becoming the currency of innovation. No trust, no ROI. The focus on governance is really key, and [SAS is] making sure the agents are trustworthy.”

Here’s the complete video interview, part of News’s and theCUBE’s coverage of SAS Innovate:

(* Disclosure: TheCUBE is a paid media partner for the SAS Innovate event. Neither SAS Institute Inc., the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or News.)

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